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Learn how to transform raw data into structured, actionable context for AI agents in this comprehensive webinar featuring Kevin Van Gundy and William Lyon from Open Data Science. Discover why agent memory has become a critical capability that determines an AI system's ability to recall, reason, and act on relevant information effectively. Explore the growing importance of knowledge graphs and contextual retrievers in making agents smarter, faster, and more trustworthy through real-world applications and data science experiences. Follow a hands-on walkthrough using Hypermode's open-source tools to build agent-ready context, including crafting retrievers and feature stores, and designing tools that expose graph data in ways agents can meaningfully utilize. Examine key design decisions, trade-offs, and lessons learned from actual implementations through live demonstrations. Understand the fundamental role of memory as a core capability for powerful agents, learn techniques for exposing graph data meaningfully to agents in live environments, and master the art of designing and curating tools that align with your agents' worldviews and goals. Whether you're building your first AI agent or seeking to enhance how existing agents reason and act, gain practical insights into overcoming the major challenge of converting unstructured data into the structured, useful context that modern AI systems require to perform effectively.
